<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LAuReL: Learned Augmented Residual Layer · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2411.07501/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2411.07501/feed.xml" rel="self" type="application/rss+xml" /><item><title>LAuReL: Learned Augmented Residual Layer — mentioned by cpldcpu</title><link>https://news.ycombinator.com/item?id=46590030</link><guid isPermaLink="false">urn:hackerpapers:mention:2411.07501:46590030</guid><pubDate>Mon, 12 Jan 2026 15:49:22 GMT</pubDate><description>&lt;p&gt;May be worth pointing out, that this is not the first residual connection innovation to be in production. Gemma 3n is also using a low-rank projection of the residual stream called LAuReL. Google did not publicize this too much, I noted it when poking around in the model file. https://arxiv.org/pdf/2411.07501v3 https://old.reddit.com/r/LocalLLaMA/comments/1kuy45r/gemma_3... Seems to be what they call LAuReL-LR in the paper, with D=2048 and R=64&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2411.07501/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
